Improving network lifetime using sensors with adjustable sensing ranges

Cardei, Mihaela; Wu, Jie; Lu, Mingming

doi:10.1504/ijsnet.2006.010833

Cited by 111 publications

(84 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On one hand, they represent the most natural random instance family where greedy heuristics (such as the MST-based one, see [17]) have a bad behaviour [19]. On the other hand, random geometric distributions provide a good model for well-spread networks located on 2-dimensional regions [7,8,17,21].…”

Section: Our Resultsmentioning

confidence: 99%

“…Several other problems concerning network lifetime have been studied in the literature [7,8,21]. Their definitions vary depending on the particular node technology (i.e., fixed or adjustable node power) and on the required connectivity or covering property.…”

Section: The Max Lifetime Problemmentioning

confidence: 99%

“…. , r k } (with 0 < r 1 < r 2 < ... < r k ) that depends on the particular adopted technology (see [7,8,24]). Clearly, the maximal range value r k in Γ must be sufficiently large to guarantee that at least one feasible solution exists.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Maximizing the Number of Broadcast Operations in Random Geometric Ad Hoc Wireless Networks

Calamoneri

Clementi

Fusco

et al. 2011

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

We consider static ad-hoc wireless networks whose nodes, equipped with the same initial battery charge, may dynamically change their transmission range. When a node v transmits with range r(v), its battery charge is decreased by β r(v) 2 where β > 0 is a fixed constant. The goal is to provide a range assignment schedule that maximizes the number of broadcast operations from a given source (this number is denoted as the length of the schedule). This maximization problem, denoted as Max LifeTime, is known to be NP-hard and the best algorithm yields worst-case approximation ratio Θ(log n), where n is the number of nodes of the network. We consider random geometric instances formed by selecting n points independently and uniformly at random from a square of side length √ n in the Euclidean plane.We present an efficient algorithm that constructs a range assignment schedule having length not smaller than 1/12 of the optimum with high probability. Then we design an efficient distributed version of the above algorithm where nodes initially know * An extended abstract of this work has been presented at OPODIS 2007. Research partially supported by the European Union under the Project IP-FP6-015964 AE-OLUS.† Dipartimento di Informatica, Sapienza Università di Roma.E-mail: {calamo, fusco, silver}@di.uniroma1.it.‡ Dipartimento di Matematica, Università degli Studi di Roma "Tor Vergata". E-mail: clementi@mat.uniroma2.it. n and their own position only. The resulting schedule guarantees the same approximation ratio achieved by the centralized version thus obtaining the first distributed algorithm having provably-good performance for this problem.

show abstract

Section: Our Resultsmentioning

confidence: 99%

Section: The Max Lifetime Problemmentioning

confidence: 99%

See 1 more Smart Citation

Maximizing the Number of Broadcast Operations in Random Geometric Ad Hoc Wireless Networks

Calamoneri

Clementi

Fusco

et al. 2011

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

show abstract

“…Motivated by prior invocations of duty cycling [19,17,1,7,9,10], Bar-Noy et al [4] studied a duty cycle variant of OnceSC with unit batteries in which sensors must be grouped into shifts of size at most k that take turns covering [0,1]. (RoundRobin is the only possible algorithm when k = 1.)…”

Section: Introductionmentioning

confidence: 99%

Set It and Forget It: Approximating the Set Once Strip Cover Problem

2016

View full text Add to dashboard Cite

We consider the Set Once Strip Cover problem, in which n wireless sensors are deployed over a one-dimensional region. Each sensor has a fixed battery that drains in inverse proportion to a radius that can be set just once, but activated at any time. The problem is to find an assignment of radii and activation times that maximizes the length of time during which the entire region is covered. We show that this problem is NP-hard. Second, we show that RoundRobin, the algorithm in which the sensors take turns covering the entire region, has a tight approximation guarantee of 3 2 in both Set Once Strip Cover and the more general Strip Cover problem, in which each radius may be set finitely-many times. Moreover, we show that the more general class of duty cycle algorithms, in which groups of sensors take turns covering the entire region, can do no better. Finally, we give an optimal O(n 2 log n)-time algorithm for the related Set Radius Strip Cover problem, in which sensors must be activated immediately.

show abstract

“…Such results and techniques are clearly not useful for our (dynamic) Max LifeTime problem. Several other problems concerning network lifetime have been studied in the literature [7,8,20]. Their definitions vary depending on the particular node technology (i.e.…”

Section: Introductionmentioning

confidence: 99%

Maximizing the Number of Broadcast Operations in Static Random Geometric Ad-Hoc Networks

Calamoneri

Clementi

Fusco

et al.

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. We consider static ad-hoc wireless networks where nodes have the same initial battery charge and they may dynamically change their transmission range at every time slot. When a node v transmits with range r(v), its battery charge is decreased by β × r(v) 2 where β > 0 is a fixed constant. The goal is to provide a range assignment schedule that maximizes the number of broadcast operations from a given source (this number is denoted as the length of the schedule). This maximization problem, denoted as Max LifeTime, is known to be NP-hard and the best algorithm yields worst-case approximation ratio Θ(log n), where n is the number of nodes of the network [5]. We consider random geometric instances formed by selecting n points independently and uniformly at random from a square of side length √ n in the Euclidean plane. We first present an efficient algorithm that constructs a range assignment schedule having length, with high probability, not smaller than 1/12 of the optimum. We then design an efficient distributed version of the above algorithm where nodes initially know n and their own position only. The resulting schedule guarantees the same approximation ratio achieved by the centralized version thus obtaining the first distributed algorithm having provably-good performance for this problem.

show abstract

Improving network lifetime using sensors with adjustable sensing ranges

Cited by 111 publications

References 15 publications

Maximizing the Number of Broadcast Operations in Random Geometric Ad Hoc Wireless Networks

Maximizing the Number of Broadcast Operations in Random Geometric Ad Hoc Wireless Networks

Set It and Forget It: Approximating the Set Once Strip Cover Problem

Maximizing the Number of Broadcast Operations in Static Random Geometric Ad-Hoc Networks

Contact Info

Product

Resources

About